deckrun-mcp
Deckrun MCP 服务器
注意: 托管的 Deckrun 端点(
free.agenticdecks.com、deckrun-mcp-free.agenticdecks.com、api.agenticdecks.com)按需提供 — 请参阅 访问与可用性。下文记录的pip install deckrun-mcp包和本地执行路径可立即用于您自己的部署。如需托管访问权限,请提交 访问请求 — 我们会在一个工作日内回复。
Agentic Decks 的 Deckrun MCP 服务器 — 通过 Markdown 生成演示文稿 PDF、旁白视频和音频。专为 AI 智能体和 IDE 构建。
Deckrun 是一个文档执行引擎:您的 AI 编写内容,Deckrun 将其渲染为像素级完美的品牌 PDF、带旁白的 MP4 视频和 MP3 音频 — 全部源自同一个 Markdown 文件。无需幻灯片编辑器,无需视频工具,无需音频工作室。
安装: pip install deckrun-mcp
快速入门 — 无需安装
HTTP 传输已托管并就绪。只需将一个 JSON 片段添加到您的 IDE 中即可。
VS Code (GitHub Copilot Chat — v1.99+)
项目中的 .vscode/mcp.json(此文件已包含在仓库中):
{
"servers": {
"deckrun": {
"type": "http",
"url": "https://deckrun-mcp-free.agenticdecks.com/mcp/"
}
}
}Cursor
项目中的 .cursor/mcp.json:
{
"mcpServers": {
"deckrun": {
"url": "https://deckrun-mcp-free.agenticdecks.com/mcp/"
}
}
}Google Antigravity (Gemini CLI)
~/.gemini/antigravity/mcp_config.json:
{
"mcpServers": {
"deckrun": {
"serverUrl": "https://deckrun-mcp-free.agenticdecks.com/mcp/"
}
}
}Claude Code (终端)
~/.claude/settings.json:
{
"mcpServers": {
"deckrun": {
"type": "http",
"url": "https://deckrun-mcp-free.agenticdecks.com/mcp/"
}
}
}Related MCP server: mcp-ToseaAI
Stdio 安装(Claude Desktop 及其他仅支持 stdio 的客户端)
pip install deckrun-mcpClaude Desktop — ~/Library/Application Support/Claude/claude_desktop_config.json:
{
"mcpServers": {
"deckrun": {
"command": "python",
"args": ["/path/to/deckrun_mcp.py"]
}
}
}付费层级 — 添加 API 密钥:
{
"mcpServers": {
"deckrun": {
"command": "python",
"args": ["/path/to/deckrun_mcp.py"],
"env": { "DECKRUN_API_KEY": "dk_live_..." }
}
}
}订阅后,请在 agenticdecks.com 获取您的 API 密钥。
工具
免费层级(无需密钥)
工具 | 描述 |
| 获取实时幻灯片格式规范 — 布局标签、语法规则、Markdown 示例 |
| 将 Deckrun Markdown 转换为 PDF。返回一个公共 URL(90 天有效期) |
付费层级(已设置 DECKRUN_API_KEY)
包含所有免费工具,外加:
工具 | 描述 |
| Markdown → 带旁白的 MP4(异步,返回 |
| 幻灯片备注 → MP3 旁白(异步,返回 |
| 轮询异步任务状态,直到 |
| 计划名称、已用/剩余渲染单元、激活的附加组件 |
| 检查 Deckrun Markdown 并获取预检 RU 估算 |
| 列出可用的幻灯片/文档主题(系统 + 自定义) |
| 列出可用的旁白语音 — ID、名称、层级、语言 |
示例提示词
配置完成后,您可以询问 AI:
"Create a 6-slide deck on the future of edge computing"
AI 将调用 get_slide_format 来学习语法,编写 Markdown,调用 generate_slide_deck,并回复一个可点击的 PDF 链接。
HTTP 端点
层级 | MCP 端点 |
免费 |
|
付费 |
|
发现:GET <endpoint> 以 JSON 格式返回服务器元数据。
链接
Agentic Decks — 产品主页
免费层级 — 立即生成 PDF,无需注册
幻灯片背景设计器 — 设计幻灯片背景的免费工具
博客:从 Claude Code 生成免费 PDF — 分步指南
幻灯片格式参考 — 布局标签、语法规则、示例
定价 — 计划起价为每月 $25
文档 — API 文档和操作指南
PyPI —
pip install deckrun-mcp
Available Tools
2 toolsgenerate_slide_deckA
Convert Deckrun Markdown into a PDF slide deck. Call get_slide_format first to learn the correct Markdown format. Then call this tool with the completed Markdown. Returns: url (public PDF, 90-day expiry), slug, slides (count), warnings (non-fatal notices to self-correct), schema_version. Limits: max 10 slides, 50 KB Markdown. Slides separated by --- on its own line.
| Name | Required | Description | Default |
|---|---|---|---|
| markdown | Yes | Complete slide deck in Deckrun Markdown format. Must start with a title slide using <!-- <title-slide /> -->. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. Discloses return values (url with expiry, slug, slides count, warnings, schema_version) and non-fatal notices. Could mention whether operation is destructive, but creation is implied.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Concise, well-structured sentences. Front-loads main action, then details prerequisites, return fields, and limits. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Complete for a simple tool with one parameter and no output schema. Covers prerequisites, limits, return values, and warnings. No gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage 100% with one parameter. Description adds crucial formatting constraint (must start with title slide using specific comment) and reiterates limits beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it converts Deckrun Markdown into a PDF slide deck, distinct from sibling get_slide_format which teaches the format.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly instructs to call get_slide_format first, provides limits (max 10 slides, 50 KB), and explains return fields including warnings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_slide_formatA
Fetch the authoritative Deckrun slide format specification. Call this first to learn all layout tags, Markdown syntax, and rules before writing slides. Returns JSON with layout_tags, surface_syntax, example_markdown, and limits.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must bear full burden. It states the tool returns JSON with specific fields, but does not explicitly declare it as read-only or side-effect-free, nor mention any auth or rate limits. The nature of the tool is apparent, but some behavioral detail is missing.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with action and purpose. Every sentence provides essential information with no redundancy or waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description fully specifies the return structure (layout_tags, surface_syntax, example_markdown, limits). This is complete for a simple format-fetching tool with zero parameters.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters exist (0 params, 100% schema coverage). Baseline is 4. The description adds value by listing the return fields (layout_tags, surface_syntax, etc.), which helps the agent interpret the output beyond the empty schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool fetches the authoritative Deckrun slide format specification, with specific verb 'Fetch' and resource 'slide format specification'. It distinguishes from sibling 'generate_slide_deck' by indicating this is a preliminary step.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says 'Call this first to learn... before writing slides', providing clear when to use. Does not explicitly state when not to use or mention alternatives aside from the implied sibling tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
2 tool updates
v1.1.1- First observed
generate_slide_deck - First observed
get_slide_format
TDQS
The two tools have completely distinct purposes: one provides the format specification, the other generates the slide deck. No overlap in functionality.
Both tool names follow a consistent verb_noun pattern: 'generate_slide_deck' and 'get_slide_format'. Conventions are uniform.
With only 2 tools, the server feels minimal. While it covers the core workflow (get format, generate), the count is low for a full-featured service, but not extreme.
The tool set covers the essential flow: fetch format then generate. However, it lacks tools for managing or revising decks, leaving notable gaps for repeated use.
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Related MCP Connectors
Presentations.AI MCP server — create designed slide decks from a topic, text, or document.
MCP server for progressive tool usage at any scale (see https://klavis.ai)
Remote MCP server for supportsheep: run AI interviews and manage support content for your blog.
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